Dependency of human target detection performance on clutter and quality of supporting image analysis algorithms in a video surveillance task

Samuel Huber; Patrick Dunau; Peter Wellig; Karin Stein

doi:10.1117/12.2278342

5 October 2017 Dependency of human target detection performance on clutter and quality of supporting image analysis algorithms in a video surveillance task

Samuel Huber, Patrick Dunau, Peter Wellig, Karin Stein

Author Affiliations +

Proceedings Volume 10432, Target and Background Signatures III; 104320F (2017) https://doi.org/10.1117/12.2278342
Event: SPIE Security + Defence, 2017, Warsaw, Poland

Abstract

Background: In target detection, the success rates depend strongly on human observer performances. Two prior studies tested the contributions of target detection algorithms and prior training sessions. The aim of this Swiss-German cooperation study was to evaluate the dependency of human observer performance on the quality of supporting image analysis algorithms. Methods: The participants were presented 15 different video sequences. Their task was to detect all targets in the shortest possible time. Each video sequence showed a heavily cluttered simulated public area from a different viewing angle. In each video sequence, the number of avatars in the area was altered to 100, 150 and 200 subjects. The number of targets appearing was kept at 10%. The number of marked targets varied from 0, 5, 10, 20 up to 40 marked subjects while keeping the positive predictive value of the detection algorithm at 20%. During the task, workload level was assessed by applying an acoustic secondary task. Detection rates and detection times for the targets were analyzed using inferential statistics. Results: The study found Target Detection Time to increase and Target Detection Rates to decrease with increasing numbers of avatars. The same is true for the Secondary Task Reaction Time while there was no effect on Secondary Task Hit Rate. Furthermore, we found a trend for a u-shaped correlation between the numbers of markings and RTST indicating increased workload. Conclusion: The trial results may indicate useful criteria for the design of training and support of observers in observational tasks.

Citation Download Citation

Samuel Huber, Patrick Dunau, Peter Wellig, and Karin Stein "Dependency of human target detection performance on clutter and quality of supporting image analysis algorithms in a video surveillance task", Proc. SPIE 10432, Target and Background Signatures III, 104320F (5 October 2017); https://doi.org/10.1117/12.2278342

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available